In recent years, numerous architectures of lightweight robots have been proposed. The avowed aim of this new generation of robot is to interact with human operators while carrying out a task. The robot and the operator therefore share the same work space, and this implies new problematic issues pertaining to the safety of the operator. Indeed, movements of the robot with large dynamic range can notably limit the access zone near the robot.
A general problematic issue relating to manipulator robots pertains to the detection of collisions between the robot and its environment. Indeed, with the aim of improving the operating security of the robot, it is important to be able to rapidly detect collisions between the robot and its environment so as to minimize the possible damage by applying suitable post-impact strategies.
Known collision detection algorithms are usually based on the comparison of measurements with a model, making it possible to create a signal called a “residual” and which constitutes an image of the collision. The mathematical modeling of the system never being perfectly representative of the real behavior of the robot, the residual is marred by errors, and the detection strategies must impose the use of safety margins (manifested in practice by thresholds) in order to be robust in relation to these errors. This avoids the occurrence of false alerts. But on account of these conservative margins, the robot loses its sensitivity to collisions.